Management of Persistent Low-Suspicion Cervical Lymphadenopathy in Pediatric Patients.

INTRODUCTION: Cervical lymphadenopathy in children is typically self-limited; however, the management of persistent lymphadenopathy remains unclear. This study aimed to evaluate the management and outcomes of patients with persistent cervical lymphadenopathy. METHODS: Single-institution, retrospective review of children <18 years undergoing ultrasound (US) for cervical lymphadenopathy from 2013 to 2021 was performed. Patients were stratified into initial biopsy, delayed biopsy, or no biopsy groups. Clinical characteristics and workup were compared, and multivariate analyses were performed to assess predictors of delayed biopsy. RESULTS: 568 patients were identified, with 493 patients having no biopsy, 41 patients undergoing initial biopsy, and 34 patients undergoing delayed biopsy. Presenting symptoms differed: no biopsy patients were younger, were more likely to present to the emergency department, and had clinical findings often associated with acute illness. Patients with USs revealing abnormal vascularity or atypical architecture were more likely to be biopsied. History of malignancy, symptoms >1 week but <3 months, and atypical or change in architecture on US was associated with delayed biopsy. Patients with long-term follow-up (LTF) were followed for a median of 99.0 days. Malignancies were identified in 12 patients (2.1%). All malignancies were diagnosed within 14 days of presentation, and no malignancies were identified in LTF. CONCLUSIONS: Patients with persistent low suspicion lymphadenopathy are often followed for long durations; however, in this cohort, no malignancies were diagnosed during LTF. We propose an algorithm of forgoing a biopsy and employing primary care surveillance and education, which may be appropriate for these patients in the proper setting.

Isolated cervical lymph node sarcoidosis: a diagnostic challenge of a case report.

BACKGROUND: Sarcoidosis is a granulomatous disorder involving multi-systemic organs. Patients invariably have lung involvement but some may have extrapulmonary disease. Rarely, cervical lymphadenopathy is the only sign without mediastinal or pulmonary abnormalities. CASE PRESENTATION: We report a Malay male who complained of neck swelling exclusively. On imaging, multiple enlarged cervical lymph nodes deep to the sternocleidomastoid muscle were seen. An excision biopsy revealed non-caseating granulomas with epithelioid macrophages. Extensive investigations led to the diagnosis of isolated cervical lymph node sarcoidosis. CONCLUSIONS: Sarcoidosis can present as cervical lymphadenopathy alone, without mediastinal or lung disease. The presence of epithelioid granulomas on histopathology warrants the exclusion of other granulomatous diseases. Isolated cervical lymph node sarcoidosis is only diagnosed in the presence of consistent clinical and radiological findings. In this case, close monitoring for systemic sarcoidosis is important as it can manifest later in life.

Post-pandemic healthcare for COVID-19 vaccine: Tissue-aware diagnosis of cervical lymphadenopathy via multi-modal ultrasound semantic segmentation.

With the widespread deployment of COVID-19 vaccines all around the world, billions of people have benefited from the vaccination and thereby avoiding infection. However, huge amount of clinical cases revealed diverse side effects of COVID-19 vaccines, among which cervical lymphadenopathy is one of the most frequent local reactions. Therefore, rapid detection of cervical lymph node (LN) is essential in terms of vaccine recipients' healthcare and avoidance of misdiagnosis in the post-pandemic era. This paper focuses on a novel deep learning-based framework for the rapid diagnosis of cervical lymphadenopathy towards COVID-19 vaccine recipients. Existing deep learning-based computer-aided diagnosis (CAD) methods for cervical LN enlargement mostly only depend on single modal images, e.g., grayscale ultrasound (US), color Doppler ultrasound, and CT, while failing to effectively integrate information from the multi-source medical images. Meanwhile, both the surrounding tissue objects of the cervical LNs and different regions inside the cervical LNs may imply valuable diagnostic knowledge which is pending for mining. In this paper, we propose an Tissue-Aware Cervical Lymph Node Diagnosis method (TACLND) via multi-modal ultrasound semantic segmentation. The method effectively integrates grayscale and color Doppler US images and realizes a pixel-level localization of different tissue objects, i.e., lymph, muscle, and blood vessels. With inter-tissue and intra-tissue attention mechanisms applied, our proposed method can enhance the implicit tissue-level diagnostic knowledge in both spatial and channel dimension, and realize diagnosis of cervical LN with normal, benign or malignant state. Extensive experiments conducted on our collected cervical LN US dataset demonstrate the effectiveness of our methods on both tissue detection and cervical lymphadenopathy diagnosis. Therefore, our proposed framework can guarantee efficient diagnosis for the vaccine recipients' cervical LN, and assist doctors to discriminate between COVID-related reactive lymphadenopathy and metastatic lymphadenopathy.

Hodgkin Lymphoma after Disseminated Mycobacterium genavense Infection, Germany.

Mycobacterium genavense infection, a rare nontuberculous mycobacteria infection, occurs in heavily immunocompromised patients (i.e., those with advanced HIV disease, genetic disorders, or acquired immunologic disorders and those undergoing immunosuppressive therapy). We report a case of disseminated M. genavense infection preceding Hodgkin lymphoma in a patient without obvious risk factors for this infection.

Deep learning radiomics of dual-modality ultrasound images for hierarchical diagnosis of unexplained cervical lymphadenopathy.

BACKGROUND: Accurate diagnosis of unexplained cervical lymphadenopathy (CLA) using medical images heavily relies on the experience of radiologists, which is even worse for CLA patients in underdeveloped countries and regions, because of lack of expertise and reliable medical history. This study aimed to develop a deep learning (DL) radiomics model based on B-mode and color Doppler ultrasound images for assisting radiologists to improve their diagnoses of the etiology of unexplained CLA. METHODS: Patients with unexplained CLA who received ultrasound examinations from three hospitals located in underdeveloped areas of China were retrospectively enrolled. They were all pathologically confirmed with reactive hyperplasia, tuberculous lymphadenitis, lymphoma, or metastatic carcinoma. By mimicking the diagnosis logic of radiologists, three DL sub-models were developed to achieve the primary diagnosis of benign and malignant, the secondary diagnosis of reactive hyperplasia and tuberculous lymphadenitis in benign candidates, and of lymphoma and metastatic carcinoma in malignant candidates, respectively. Then, a CLA hierarchical diagnostic model (CLA-HDM) integrating all sub-models was proposed to classify the specific etiology of each unexplained CLA. The assistant effectiveness of CLA-HDM was assessed by comparing six radiologists between without and with using the DL-based classification and heatmap guidance. RESULTS: A total of 763 patients with unexplained CLA were enrolled and were split into the training cohort (n=395), internal testing cohort (n=171), and external testing cohorts 1 (n=105) and 2 (n=92). The CLA-HDM for diagnosing four common etiologies of unexplained CLA achieved AUCs of 0.873 (95% CI: 0.838-0.908), 0.837 (95% CI: 0.789-0.889), and 0.840 (95% CI: 0.789-0.898) in the three testing cohorts, respectively, which was systematically more accurate than all the participating radiologists. With its assistance, the accuracy, sensitivity, and specificity of six radiologists with different levels of experience were generally improved, reducing the false-negative rate of 2.2-10% and the false-positive rate of 0.7-3.1%. CONCLUSIONS: Multi-cohort testing demonstrated our DL model integrating dual-modality ultrasound images achieved accurate diagnosis of unexplained CLA. With its assistance, the gap between radiologists with different levels of experience was narrowed, which is potentially of great significance for benefiting CLA patients in underdeveloped countries and regions worldwide.

Kikuchi-Fujimoto disease presenting in a patient with SARS-CoV-2: a case report.

BACKGROUND: We present a yet to be described association of SARS-CoV-2 infection with Kikuchi-Fujimoto disease. CASE PRESENTATION: A 32-year-old physician with history of SARS-CoV-2 infection presented to the emergency department with 2 weeks of fever, chills, and right sided cervical lymphadenopathy. He was treated empirically for presumed folliculitis with worsening of symptoms leading to repeat presentation to the emergency department. Extensive workup was unrevealing of an infectious cause and needle biopsy of the lesion was unrevealing. An excisional lymph node biopsy revealed follicular hyperplasia with necrotic foci showing abundance of histiocytes at the edge of necrosis with CD8 predominance of T-cells. Final diagnosis was deemed to be Kikuchi-Fujimoto disease. Antibiotic therapy was discontinued, and the patient's symptoms resolved with steroid therapy and expectant management. CONCLUSIONS: This is the first report of a patient developing Kikuchi-Fujimoto disease following SARS-CoV-2 infection. Clinicians should be aware of Kikuchi-Fujimoto disease as a possibility when approaching patients with hyper-inflammatory states who present with cervical lymphadenopathy.

Application of neck ultrasound in the diagnosis of sarcoidosis.

OBJECTIVE: To explore the significance of neck ultrasound (NUS) combined with contrast-enhanced ultrasound (CEUS) in the diagnosis of sarcoidosis. METHODS: 88 patients with evidence of intrathoracic lymphadenopathy and suspected sarcoidosis with enlarged cervical lymph nodes underwent NUS, CEUS, fine-needle aspiration and core needle biopsy when technically feasible were retrospectively analyzed in this study. Seven characteristics such as enhanced mode (EM), resolution time, color Doppler flow imaging (CDFI), fading time, peaking state-uniformity, strengthen the area and symmetry were considered to perform the logistic regression model. RESULTS: Of 88 patients included in this study, sarcoidosis was accounted in 20 cases, tuberculosis in 23 cases, malignancy in 22 cases and inflammatory lymph node in 23 cases. There were statistically significant differences in symmetry, lymphatic hilum, homogeneity, CDFI pattern and elasticity score between the sarcoidosis and non-sarcoidosis groups via NUS. Similarly, we also acknowledged a statistically significant differences in EM, homogeneity, presence or absence of necrosis between the sarcoidosis and non-sarcoidosis groups via CEUS to further group the non-sarcoidosis into tuberculosis, malignancy or inflammatory disorder. The percentage correction of prediction was 90% (18/20). CONCLUSION: NUS combined with CEUS has characteristic features in sarcoidosis with cervical lymph node involvement, which is helpful for its diagnosis and differential diagnosis. The binary classification model of NUS combined with CEUS features can help differentiate sarcoidosis from non-sarcoidosis groups.

Appraisal of clinical practice guidelines for the evaluation and management of neck masses in children.

AIM: The purpose of this systematic review was to use the Appraisal of Guidelines for Research and Evaluation tool to assess the methodological quality of clinical practice guidelines (CPGs) for the workup and management of paediatric neck masses. METHODS: MEDLINE, Embase, Cochrane and grey literature were searched to identify CPG incorporating paediatric neck masses. Four authors with previous training of the Appraisal of Guidelines for Research and Evaluation tool evaluated the included studies. RESULTS: Nine studies met inclusion criteria. The highest scoring domains were 'Scope and Purpose' (74.0 ± 4.5) and 'Clarity of Presentation' (72.9 ± 6.3). The lowest scoring domains were 'Rigour and Development' (18.8 ± 7.5) and 'Applicability' (23.7 ± 6.1). One study was 'High' quality, three received scores of 'Average' and five were found to be 'Low' quality. CONCLUSION: The majority of paediatric neck mass CPGs were low to average quality. The domains in need of greatest improvement were 'Rigour and Development' and 'Applicability', suggesting significant concerns in current CPGs focused on paediatric neck masses.

Utility of sonography for identifying metastatic cervical adenopathy in children with differentiated thyroid carcinoma at presentation.

BACKGROUND: No study has evaluated the diagnostic accuracy of sonography for the depiction of metastatic cervical adenopathy in children with differentiated thyroid carcinoma at presentation or determined which sonographic features are most useful. OBJECTIVE: To evaluate the diagnostic accuracy of sonography for identifying metastatic cervical adenopathy in children with differentiated thyroid carcinoma at presentation and to determine the most useful sonographic features. MATERIALS AND METHODS: We evaluated cervical lymph node sonography and histology in children with proven thyroid carcinoma in a 10-year period. We excluded children in whom a preoperative sonogram was not available and those who did not have surgical resection of lymph nodes. We used histology as the gold standard. On sonography, we analyzed the size, shape, echotexture and vascularity of the lymph nodes and correlated these findings with the histology. RESULTS: We reviewed sonograms and histology of resected lymph nodes in 52 children and adolescents with proven differentiated thyroid carcinoma (33 females; ages 5-18 years, mean 13.2 years). Metastatic cervical lymph node disease was proved on histology in 33/52 (64%) of our patients at presentation. Sonographic findings correctly predicted whether the nodes were histologically involved with metastatic disease in 42/52 (81%). Sensitivity of sonography was 79%, specificity 84%, positive predictive value (PPV) 90%, negative predictive value (NPV) 70% and accuracy 81%. A significant association was seen between round shape (P=0.0002), abnormal echotexture (P≤0.0001) and vascularity (P≤0.0001), and abnormal lymph node histology. Importantly, in 11/26 (47%) patients with sonographic and histologically proven abnormal nodes, the nodes were normal in size and shape and the presence of metastatic involvement was recognized sonographically only on the basis of abnormal echogenicity and vascularity. CONCLUSION: Sonography has a high accuracy, specificity and PPV for identifying metastatic cervical lymph node involvement in children with differentiated thyroid carcinoma at presentation. Most of the abnormal lymph nodes were round in shape and had abnormal echogenicity and vascularity. Importantly, this paper emphasizes that in children, nodes with histologically proven metastases from differentiated thyroid carcinoma can be normal in size and shape. In these patients the presence of metastatic involvement might be recognized sonographically only on the basis of abnormal echogenicity and vascularity.

Cystic cervical lymph nodes of papillary thyroid carcinoma, tuberculosis and human papillomavirus positive oropharyngeal squamous cell carcinoma: utility of deep learning in their differentiation on CT.

OBJECTIVES: Cervical lymph nodes with internal cystic changes are seen with several pathologies, including papillary thyroid carcinoma (PTC), tuberculosis (TB), and HPV-positive oropharyngeal squamous cell carcinoma (HPV+OPSCC). Differentiating these lymph nodes is difficult in the absence of a known primary tumor or reliable medical history. In this study, we assessed the utility of deep learning in differentiating the pathologic lymph nodes of PTC, TB, and HPV+OPSCC on CT. METHODS: A total of 173 lymph nodes (55 PTC, 58 TB, and 60 HPV+OPSCC) were selected based on pathology records and suspicious morphological features. These lymph nodes were divided into the training set (n = 131) and the test set (n = 42). In deep learning analysis, JPEG lymph node images were extracted from the CT slice that included the largest area of each node and fed into a deep learning training session to create a diagnostic model. Transfer learning was used with the deep learning model architecture of ResNet-101. Using the test set, the diagnostic performance of the deep learning model was compared against the histopathological diagnosis and to the diagnostic performances of two board-certified neuroradiologists. RESULTS: Diagnostic accuracy of the deep learning model was 0.76 (=32/42), whereas those of Radiologist 1 and Radiologist 2 were 0.48 (=20/42) and 0.41 (=17/42), respectively. Deep learning derived diagnostic accuracy was significantly higher than both of the two neuroradiologists (P < 0.01, respectively). CONCLUSION: Deep learning algorithm holds promise to become a useful diagnostic support tool in interpreting cervical lymphadenopathy.

[Analysis of the phenotypic heterogeneity of CD123-positive cells in Kikuchi-Fujimoto disease using a sequential immunoperoxidase labeling and erasing method]. / Analiz fenotipicheskoi geterogennosti CD123-pozitivnykh kletok pri bolezni Kikuchi­Fudzhimoto s pomoshch'yu metoda posledovatel'nogo immunoperoksidaznogo okrashivaniya i stiraniya.

Kikuchi-Fujimoto disease (KFD) is a rare disease that is clinically manifested mainly by fever and lymphadenopathy. KFD was originally believed to occur primarily in East Asia women, this disease was subsequently described in all ethnic groups worldwide. The important differential diagnostic feature of KFD is the detection of CD123-expressing plasmocytoid dendritic cells (PDCs) in the tissue of the affected lymph node. The standard immunohistochemical staining method has sufficient sensitivity and specificity to detect CD123, but it gives no way of judging the possible phenotypic heterogeneity of cells with CD123 expression. OBJECTIVE: To identify the phenotypic heterogeneity of CD123-expressing cells in the affected lymph nodes in patients with KFD by a sequential immunoperoxidase labeling and erasing (SIMPLE) method. MATERIAL AND METHODS: Excision biopsies of lymph nodes were examined in 3 patients with KFD. After an immunohistochemical reaction using a single antibody, the tissue specimen was digitized with a Pannoramic 250 Flash III scanner (3DHISTECH, Hungary), then the cover glass was removed from the section, the specimen was hydrated and placed in a specialized buffer. Then the following primary antibody was applied to the washed tissue specimen and further immunohistochemical reaction and scanning were performed. As a result, each tissue specimen was sequentially stained in reactions with 4 antibodies. The microphotographs of specimens stained in a reaction with anti-CD123 antibody showed positive cells for their identification in the Pannoramic Viewer program (3DHISTECH, Hungary) on the remaining microphotographs displaying the expression of the other 3 markers. The selected fields of view were exported to a JPG format. RESULTS: Assessing the co-expression of the antigens CD123, MNDA, CD68, and TCL1A detected 4 CD123+ cell subpopulations: No. 1. CD68+/ MNDA+/ TCL1A+; No. 2. CD68+/ MNDA+/ TCL1A-; No. 3. CD68+/ MNDA-/ TCL1A+; No. 4. CD68-/ MNDA-/ TCL1A+. CONCLUSION: SIMPLE has shown the phenotypic heterogeneity of CD123-positive cells (some of them may be PDCs) and could identify 4 immunophenotypically distinct subpopulations in the affected lymph nodes in patients with KFD. Further investigations are needed to define the role of subpopulations in the pathogenesis of KFD and other diseases.

Prediction Model for the Differential Diagnosis of Kawasaki Disease and Acute Cervical Lymphadenitis in Patients Initially Presenting with Fever and Cervical Lymphadenitis.

OBJECTIVES: To distinguish early-stage lymph node first presentation of Kawasaki disease from acute cervical lymphadenitis, we developed an algorithm using sequential laboratory marker levels and radiologic findings. STUDY DESIGN: Data were obtained from pediatric inpatients initially presenting with fever and cervical lymphadenopathy. Discriminative factors for the differential diagnosis of acute cervical lymphadenitis and lymph node first presentation of Kawasaki disease were identified from intergroup comparison or univariate logistic regression analysis. A model for differentiating between lymph node first presentation of Kawasaki disease and acute cervical lymphadenitis was constructed using decision-tree analysis. RESULTS: Patients were divided into 2 cohorts: training (206 patients) and validation (103 patients) cohorts. A decision-tree model developed from the data of the training cohort included 3 determinants: neck computed tomography- or ultrasonography-defined abscess, percentage change in C-reactive protein level, and percentage change in neutrophil count. The prediction power of our decision-tree model for the validation cohort was superior to that of previously known laboratory markers (sensitivity of 89.5%, specificity of 88.9%, positive predictive value of 95.8%, negative predictive value of 75.0%, overall accuracy of 89.3%, and a Youden index of 0.784). CONCLUSIONS: A decision-tree model could differentiate lymph node first presentation of Kawasaki disease from acute cervical lymphadenitis with an increased accuracy. External validation based on multicenter data is needed before clinical application.

Analysis of the causes of cervical lymphadenopathy using fine-needle aspiration cytology combining cell block in Chinese patients with and without HIV infection.

BACKGROUND: Cervical lymphadenopathy refers to a frequently observed clinical presentation in numerous pathological conditions. A wide spectrum of diseases can cause cervical lymphadenopathy, irrespective of the fact that the patients are infected with HIV or not. The present study focuses on validating whether the causes of cervical lymphadenopathy differ significantly in HIV and non-HIV patients by using fine-needle aspiration cytology (FNAC) combining cell block. METHODS: A total of 589 patients with cervical lymphadenopathy were recruited in the FNA clinic. The samples were obtained by an auto-vacuumed syringe that benefited the sampling more materials. The cytological smears were prepared by Hematoxylin and Eosin (HE), Periodic Acid Schiff (PAS), Gomori's methenamine silver (GMS) and acid-fast staining. Cell blocks were made if required, and immunohistochemistry stain was performed on the cell block section. RESULTS: The study found 453 (76.9%) patients with HIV and 136 (23.1%) patients without HIV infection. The average age of HIV-infected patients was 34.8 ± 10.2 years, which was significantly lower than that of non-HIV-infected patients (42.9 ± 18.1 years) (p < 0.01). Of all patients infected with HIV, 390 (86.1%) were males. This proportion was significantly higher than that of non-HIV-infected patients [65/136 (47.8%)] (p < 0.01). The major causes of cervical lymphadenopathy in HIV positive patients were mycobacterial infection (38.4%), reactive hyperplasia (28.9%), non-specific inflammation (19.9%), and malignant lesions (4.2%). In contrast, the most common causes in HIV negative patients were reactive hyperplasia (37.5%), malignancy (20.6%), non-specific inflammation (19.1%) and mycobacterial infection (12.5%). Opportunistic infections such as non-tuberculous mycobacteria (4.2%), cryptococcosis (1.5%), Talaromyces marneffei (1.5%) and other fungi (0.4%) were found only in HIV-infected individuals. Non-Hodgkin's lymphoma (2.4%) was the most common malignant lesion in patients with HIV infection, followed by Kaposi's sarcoma (0.9%) and metastatic squamous cell carcinomas (0.7%). However, the most common malignancy in non-HIV-infected patients was metastatic carcinomas (14%) including small cell carcinomas, adenocarcinomas, squamous cell carcinomas and hepatocellular carcinoma, which were noticeably greater than the HIV patients (p < 0.01). CONCLUSIONS: There were significantly different causes of cervical lymphadenopathy in HIV infected and non-HIV infected patients. FNAC was a useful diagnostic method for differential diagnosis of cervical lymphadenopathy.

Kikuchi Disease: A Case Report.

BACKGROUND: Kikuchi disease, also known as Kikuchi-Fujimoto disease, is a rare, benign cause of cervical lymphadenitis. It is characterized by painful cervical lymphadenopathy with fevers, leukopenia, and an elevated erythrocyte sedimentation rate. It is diagnosed by obtaining a biopsy specimen from a lymph node that shows characteristic histopathologic findings. CASE REPORT: We highlight a 42-year-old Japanese man who presented with persistent fevers and cervical lymphadenopathy who was misdiagnosed at multiple urgent care facilities and emergency departments. He was eventually diagnosed with Kikuchi disease after a biopsy specimen was obtained from a lymph node 1 month after his symptoms began. He was treated with hydroxychloroquine and prednisone with resolution of his symptoms. WHY SHOULD AN EMERGENCY PHYSICIAN BE AWARE OF THIS?: Although Kikuchi disease has been previously described in various specialty medical journals, the published literature on Kikuchi disease in emergency medicine is relatively scarce. Given that cervical lymphadenopathy is a common presentation to emergency departments, it is important for emergency physicians to be cognizant of Kikuchi disease in the differential diagnosis of cervical lymphadenopathy to prevent misdiagnoses and unnecessary treatments.

Differentiation of Kawasaki Disease From Other Causes of Fever and Cervical Lymphadenopathy: A Diagnostic Scoring System Using Contrast-Enhanced CT.

OBJECTIVE: The purpose of this study is to determine the characteristic findings of contrast-enhanced CT (CECT) of the neck in patients with Kawasaki disease (KD) and to develop a diagnostic scoring system to facilitate the diagnosis of KD versus other causes of fever and cervical lymphadenopathy. MATERIALS AND METHODS: Two blinded radiologists evaluated CECT images of 37 patients with KD and 92 patients without KD who had febrile cervical lymphadenopathy, first independently and then in consensus. Significant findings in CECT images were evaluated through cervical edema and lymph node scores. CT attenuation of the nodal low-attenuation area and its ratio to the CT attenuation of the trapezius muscle were measured. On the basis of these indexes, a diagnostic scoring system was developed to differentiate between patients with and without KD. Its diagnostic performance was determined using ROC curve analysis. RESULTS: Retropharyngeal edema, lateral cervical edema, nasopharyngeal wall edema, level IIA lymphadenopathy, and retropharyngeal lymphadenopathy were more common in patients with KD than in patients without KD (p < 0.001, < 0.001, < 0.001, 0.003, and 0.028, respectively). Level VB lymphadenopathy was more common in patients without KD (p = 0.013), and the presence of nodal low-attenuation areas with lower attenuation indexes (attenuation of nodal low-attenuation area ≤ 50 HU, or ratio of attenuation of nodal low-attenuation area to trapezius muscle attenuation ≤ 0.7) was specific to patients without KD. In cases of higher attenuation indexes and cervical edema and lymph node scores of 4 or higher, sensitivity, specificity, and accuracy of the diagnostic scoring system were 86% (32/37), 86% (79/92), and 86% (111/129), respectively, for diagnosing KD. CONCLUSION: The proposed diagnostic scoring system was useful in differentiating between patients with and without KD.

Differentiation of lymphomatous, metastatic, and non-malignant lymphadenopathy in the neck with quantitative diffusion-weighted imaging: systematic review and meta-analysis.

PURPOSE: To perform a systematic review and meta-analysis of literature comparing average apparent diffusion coefficient (ADC) for differentiating lymphomatous, metastatic, and non-malignant cervical lymphadenopathy. METHODS: We performed a comprehensive literature search of Ovid MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, and Web of Science Core Collection. Studies comparing average ADC of lymphomatous, metastatic, and non-malignant neck lymph nodes were included. The standardized mean difference and 95% confidence interval (CI) was calculated using random-effects models. In subgroup analysis of those studies applying ADC threshold for differentiation of cervical lymphadenopathy, pooled diagnostic odds ratio (DOR) and summary receiver operating characteristics (sROC) area under the curve (AUC) were determined. RESULTS: A total of 27 studies with 1165 patients were included, pooling data from 225 lymphomatous, 1162 metastatic, and 1333 non-malignant cervical lymph nodes. The average ADC values were lower in lymphomatous compared to metastatic nodes, and in metastatic compared to non-malignant nodes with a standardized mean difference of - 1.36 (95% CI: - 1.71 to - 1.01, p < 0.0001) and - 1.61 (95% CI: - 2.19 to - 1.04, p < 0.0001), respectively. In subgroup analysis, applying ADC threshold could differentiate lymphomatous from metastatic lymphadenopathy with DOR of 52.07 (95% CI 25.45-106.54) and sROC AUC of 0.936 (95% CI 0.896-0.979) and differentiate metastatic from non-malignant nodes with DOR of 39.45 (95% CI 16.92-92.18) and sROC AUC of 0.929 (95% CI 0.873-0.966). CONCLUSIONS: Quantitative assessment of ADC can help with differentiation of suspicious cervical lymph nodes, particularly in those patients without prior history of malignancy or unknown primary cancer site.

Visceral Leishmaniasis in Traveler to Guyana Caused by Leishmania siamensis, London, UK.

The parasite Leishmania siamensis is a zoonotic agent of leishmaniasis; infection in animals has been documented in Europe and the United States. Reported authochthonous human infections have been limited to Thailand. We report a case of human visceral Leishmania siamensis infection acquired in Guyana, suggesting colonization in South America.

PET and Neck Ultrasound for the Detection of Cervical Lymphadenopathy in Patients with Lung Cancer and Mediastinal Lymphadenopathy.

BACKGROUND: Cervical lymph nodes are frequently involved in patients with lung cancer and indicate inoperability. Some guidelines recommend neck ultrasound (NUS) in patients with bulky mediastinal lymphadenopathy. Positron emission tomography (PET) is indicated for patients with potentially curable disease. OBJECTIVES: We aimed to assess the diagnostic yield of NUS and the diagnostic accuracy of PET for cervical lymphadenopathy in this group with a high pre-test probability of N3 disease. METHODS: Records of all patients with lung cancer who underwent an NUS over a consecutive 5-year period were reviewed. Only patients with mediastinal lymphadenopathy on computerised tomography (CT) were included. The diagnostic accuracy of PET was assessed with NUS-guided fine needle aspiration cytology used as the reference test. RESULTS: During the study period, 123 patients met the inclusion criteria. Malignant cervical lymphadenopathy was confirmed in 49/123 (39.8% [95% CI 31.1-49.1]). PET-CT had a specificity of 81.1%, sensitivity of 87.5%, negative predictive value of 96.8% and positive predictive value of 50% for the detection of cervical lymphadenopathy, and it contributed no additional staging information in the neck area. Overall, PET led to a change in management in only 2.2% of cases. CONCLUSION: A significant proportion of patients with lung cancer and mediastinal lymphadenopathy have cervical lymphadenopathy detected by NUS. In this group of patients, PET offers minimal additional value in staging and management.

Ultrasound evaluation of cervical lymphadenopathy: Can it reduce the need of histopathology/cytopathology?

BACKGROUND: The differentiation between the causes of cervical lymphadenopathy is of paramount importance as these have different modalities of treatment with varying prognosis. The aim of this study was to evaluate the efficacy of B Mode and colour Doppler ultrasound (CDUS) to differentiate between benign and metastatic lymph nodes. METHODS: 100 patients of clinically palpable lymph nodes were evaluated with B Mode and CDUS. B Mode assessment included short-long (S:L) axis ratio, hilum, nodal border, echogenicity, intranodal necrosis and ancillary features. CDUS assessment included distribution of vascularity, resistive index (RI) and pulsatility index (PI). Statistical analysis was carried out with histopathological or cytological diagnosis as gold standard. RESULTS: B-Mode US correctly diagnosed 22/25 (88%) of the reactive lymph nodes giving it a sensitivity of 88% and specificity of 97.3%. Colour Doppler US diagnosed 23/25 (92%) reactive lymph nodes with a sensitivity of 92% and specificity of 97.3%. B-Mode underdiagnosed one case each of granulomatous disease and metastasis as reactive node while CDUS missed out two cases of granulomatous disease as reactive lymph node. CONCLUSION: Individual parameters of B Mode when used alone were not found to be very effective in differentiating benign and malignant lymph nodes. However features of B-Mode combined together as well as color Doppler ultrasound, help in the detection of reactive lymph nodes and can be used as a diagnostic tool with good accuracy. However, they cannot be used as a diagnostic method for metastatic or tubercular nodes and cytopathology/histopathology remains the gold standard in such situations.